# Tag Info

50

I am going to recommend something that I have no doubt will get people completely up in arms and probably get people to attack me. It happened in the past and I lost many points on StackOverflow as people downvoted my answer. I certainly hope people are more open minded in the quant forum. Note - It seems that this suggestion has created some strong ...

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quandl is a new data source for all kind of econometric time series.

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I don't know how interested you are in the CME data, but I have been learning about options and volatility modeling. I have been working with delayed CME data. I have been able to extract the JSON queries and now have been able to run them in my .NET application to get data for every asset type. Exmaple of ES options data: Run the query below in Chrome ...

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Academic access to Thomson Reuters Tick History: www.sirca.org.au The Thomson Reuters Tick History database provides millisecond-timestamped tick data going back to January 1996, covering 45 million OTC and exchange-traded instruments worldwide. The database currently updates at a rate of 1 million messages per second and is around 3 Petabytes uncompressed....

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Eric Zivot's Introduction to Computational Finance and Financial Econometrics on Coursera.

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All of the answers above (unfortunately highly upvoted at this point) are missing the point. You shouldn't pick a DBMS or storage solution by general performance benchmarks, you should pick it by use case. If someone says they get a "x ms read", "y inserts per second", "k times speedup", "store n TB data" or "have m years of experience" and use that to ...

13

Khan Academy now offers finance videos (he already started with e.g. the basics of option trading strategies and arbitrage pricing):

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Accounting is a vital skill if you end up in a managerial position, and unless your career goal is to always be a cog in someone else's clockwork, then you will eventually find yourself in a managerial/senior partnership position even through quant research. I still play a critical role in my firm's quant strategies team, but here's a few things I've had to ...

12

Google and Yahoo finance have a survivorship bias -- they only include firms that are still around. I know of no free source that provides the data you seek. I get my data from Compustat and CRSP via the Wharton Resource Data Service, but these (or Bloomberg or Reuters) are likely too expensive for an individual. Have you asked your broker if they will sell ...

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To get a consolidated feed of most of the data feeds here use Quandl. This is free for limited amount of requests per day.

11

There is certainly much more to quantitative finance than technical analysis, and a previous question does a decent job of outlining the different areas, as does the wikipedia on "quantitative analyst". Even for what wikipedia terms an "algorithmic trading quant" or what Mark Joshi terms a "statistical arbitrage quant", technical analysis is just one tool ...

11

The standard answer is going to be that for time series, you want a column store database. These are optimized for range queries (ie: give me everything between two timestamps) because crucially, they store data along one of the dimensions (which you must choose, usually time) contiguously on disk, and thus reads are extremely fast. The alternative, when ...

10

Somewhat more economic data can be found at e.g.: The World Bank The United Nations The OECD More financial: The IMF European Union / EFTA / EMU data: Eurostat European Central Bank (financial) Data from these sources is all freely available. You can also play with data from many of these sources using the Google Public Data Explorer.

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This is the canonical Arrow-Pratt "portfolio" model. Couple of points on terminology: For a function $u$, we define the risk aversion function by $r_u(x):=-\frac{u''(x)}{u'(x)}$. In your utility function, $r_u(x) = \lambda$; hence, it is a constant absolute risk aversion utility and $\lambda$ is the "coefficient of risk aversion," not the "risk ...

10

Pull-to-par says that the bond's price will gradually converge toward par (100% of face value) when yield is unchanged. This process is also known as accretion for a bond trading at a discount (since its price gradually goes higher toward par) and amortization for a bond trading at a premium (since its price gradually declines toward par). Pull-to-par says ...

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Quandl is a free one, with good economic and market data and an API http://www.quandl.com/

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Have a look here: http://www.climatelogic.com/ The method is based on a sequential F-test, see also this paper: Rodionov, S.N., 2005b: Detecting regime shifts in the mean and variance: Methods and specific examples. In: Large-Scale Disturbances (Regime Shifts) and Recovery in Aquatic Ecosystems: Challenges for Management Toward Sustainability, V. Velikova ...

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If you want to learn more about price pressure, you should look after market impact of metaorders, which is a more adequate term. Because of the microstructure (i.e. the mix of orderbboks dynamics, trading rules, participants behaviours and habits, etc), the more you buy or sell, the more you influence the price an unfavorable way (for your trades). Just ...

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There are a few things to consider: Price On average Thomson Reuters is known to be less costly than Bloomberg. One thing to consider when looking to save money is that most vendors will use some kind of ladder pricing. So if you cannot get rid of either Bloomberg or Thomson Reuters completely then you may not save as much as you expected. Technology ...

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It is not financial mathematics in general, but a scientific approach that is beneficial: quantitative views and open objective tools make transactions more transparent. It decreases information asymmetry and thus decrease transaction costs in general (bid-ask spread, prices range, volatility, etc). thanks to (good) models, the consistency between ...

9

Pull-to-par just says that a bond's (clean) price will converge towards its face value as the bonds approaches maturity. There is nothing really interesting about pull-to-par - a bond's (clean) price has to converge to its face value, because a bond with just a few days to maturity is essentially a short-term cash deposit. Look at it this way - the price of ...

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While not strictly quantitative finance, for the first year in the PhD I found this Youtube-Channel extremely helpful: http://www.youtube.com/user/mathematicalmonk I covers almost only math, but does a very good job at explaining the basics of probability theory. Most people will already have mastered that stuff, but it will surely help those unfamiliar ...

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It seems logical to me to have a Financial accounting course in a quant program. Quants can have a lot of different occupations, from derivative pricing to quant analyst in a "research" (i.e. analysis) dept. of a broker, a risk dept., a fund (as an analyst or as a potfolio manager), or quant execution trader (the list is far longer). In the case of being ...

8

Define excess return $r^x_{it} = r_{it} - r^f_{t}$ as the return $i$ minus the risk free rate, and $f_{jt}$ similarly denotes the excess return of factor $j$ at time $t$. Let's say we have some factor model of returns where: $$r^x_{it} = \alpha_i + \sum_j \beta_{i,j} f_{jt} + \epsilon_{it}$$ F-test / GRS Test If we assume the error terms $\epsilon_{it}$ ...

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The bias comes from the paper Stambaugh (1999) and has nothing to do with small sample bias. It has to do with point (1) below. The argument goes as follows: Typical lagged explanatory variables for stock-return regressions are correlated with contemporaneous stock returns This contemporaneous correlation biases forecasting regressions First review OLS ...

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I did a fair amount of searching for a good source of historical data and I came across Norgate Investor Services. They provide the data in MetaStock format. I used the data for analysis in MATLAB via Metastockread. They have data for the US, Australia and Singapore.

7

There is a very cheap, i.e. free, way of obtaining the list of companies included in the S&P 500 at any given time. Check the revision history for the S&P 500 List updates on Wikipedia. It is ugly and unreliable but you usually get what you pay for :) ... it should be okay if you are just playing around with your own strategies. This doesn't ...

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Generally speaking, let us consider a problem where you have a series of simple payoffs $f_{K_i}(S_T)$ of strike $K_i$, $i \in I$, that depend on the value of $S_T$ at time $T$, as well as a more complex, laddered payoff $P_L(T)$ which pays a quantity $g_i(S_T)$ on regions of the form $\{K_i \leq S_T < K_{i+1}\}$ $-$ regions are delimited by the strikes ...

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Hi Quantitative Finance has in my opinion two main streams. The first is about of valuation of some derivative contracts in a consistent way. This is a theory and once paradigms accepted it is coherent, it can considered as science at the same level as economy can pretend to this kind of terminology. The second is about making (or trying to) prediction(s) ...

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Correct. All outstanding issues are held. Money only flows into an asset class via the primary market (such as an IPO, secondary offering, etc.) not on the secondary markets which are publicly traded. What is actually changing is people's willingness to buy and sell securities at various prices. When market commentators talk about money flowing into or out ...

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